Below is a table of the Brooks Falls bear chip data. We have face chips for 43 different bears. The table has a row for each bear. The columns are:

ID: the bear’s identification number

Nickname: the bear’s nickname (if it has one)

Count: the number of face chips we have for the bear

Example Face Images: a few example face chips for the bear

ID

Nickname

Count

Example Face Images

032

Chunk

16

051

Diver Jr.

1

068

7

083

Wayne Brother

21

089

Backpack

28

094

11

128

Grazer

61

132

29

151

Walker

67

171

3

201

1

218

Ugly

3

261

13

273

43

274

Overflow

4

284

16

289

51

402

8

409

Beadnose

73

410

Four-Ton

77

415

1

435

Holly

4

469

3

480

Otis

131

482

Brett

23

489

Ted

2

500

Indy

5

503

Cubadult

54

505

21

634

Popeye

16

700

Marge

4

708

Amelia

2

719

Princess

19

744

Dent

2

747

20

755

Scare D Bear

13

775

Lefty

178

813

Nostril Bear

3

814

Lurch

11

818

1

854

Divot

3

856

36

868

Wayne Brother

7

What We Need

As you can see, there are quite a few bears for which we only have a couple images. We really need more images of these bears to use them for training. We think we need at least 20 good face chips per bear, preferably from different seasons and different times of the season. We’re hoping the set we get from Katmai will fill out our set, but we can always you more!

We are also not sure if we can use the images where the bear is looking far to the left or right or down. We’re planning a few experiments to see how the various poses effect our results. If we have to filter out some of these more extreme poses, our dataset will get even smaller.

If you have decent quality photos or videos of the Brooks Falls bears, or of any other brown bears, please contact us at bearid [at] hypraptive [dot] com.

We are not using any captures from the explore.org bearcams at this time, as we don’t think the quality is sufficient. Hopefully, once we have the application working reasonably well, we can adapt it to work with the bearcams as well!